Improvement of identity adaptive recognition algorithm in visual sensor network - Na LI; Xiaoning ZHANG; Fang’e ZHU (Dianxin kexue)
When recognizing the identity in visual sensor network，it’s easily to be interfered with facial expression，illumination condition and shelter，so as to reduce the recognition accuracy.An identity adaptive recognition algorithm based on the improved minimum gray difference tree in visual sensor network was put forward.After gray processing，the minimum gray difference was used to enhance the quality of the image；cost function based on gray level was defined，the match price of each corresponding pair of gray of the image to be recognized and the specified face image were achieved，minimum gray difference tree model was set up，after two image similarity were calculated，the nearest neighbor matching algorithm was directly applied to obtain the image identity corresponding to minimum matching cost in the visual sensor network registration gallery，it was viewed as the identity to be recognized，the adaptive identity recognition was achieved in visual sensor network.Simulation results show that the proposed algorithm has high identification accuracy.